This study will use pooled cross-sectional and time-series data to assess the relationship between hospital and regional characteristics and variations in cesarean section rates in California. The hypotheses focus on the role of previously untested hospital and reimbursement variables such as financial incentives as well as on regional factors such as market structure. We will analyze five years of California hospital discharge abstract data (1983 to 1987); hospital-specific data such as size, urban/rural location, teaching status, NICU level, ownership status, occupancy rates, distribution of payment source, and relative charges for cesarean section vs. vaginal delivery; and regional data such as sociodemographic distribution, physician supply, and level of market competition. An important feature of the research design is the ability to observe changes in regional, hospital, and patient-related variables over time. We have obtained hospital discharge data for the full five year study period, including the following variables: service hospital, maternal age, diagnostic codes, procedure codes, source of payment, past obstetrical history of the mother and designation of c-section as elective or emergency surgery. An integral part of the statistical analysis will be to account initially for the effects of patient characteristics and clinical indications for c-section on a hospital's c-section rate. We will adjust each hospital's actual rate, using selected pre-delivery c-haracteristics and medical variables of the mothers to calculate the 'expected' c-section rate over the five year time period. A model then will be developed using the case-mix-adjusted C-section rates as the dependent variable. The case-mix adjustment Will insure that the observed relationships between the non-clinical explanatory variables and the cesarean rates are not a function of clinical factors. The major methodological advantage of the proposed study is that it will pool cross-sectional and time-series data, thus minimizing the problem of multicollinearity among the independent variables. This approach has not been used by any previous studies of cesarean rates.